Introduction to Statistics and Data Collection

Vocabulary flashcards covering core concepts, sampling methods, bias types, and graphical representations in introductory statistics.

Statistics

The science and art of collecting, analyzing, and drawing conclusions from data.

Individual

A person, animal, or thing that is described in a set of data.

Variable

Any attribute that can take different values for different individuals.

Categorical variable

Takes values that are labels, which place each individual into a particular group, called a category.

Quantitative variable

Takes numerical values that are quantities, such as counts or measurements.

Population

The entire group of individuals in a statistical study that we want info about.

Census

Collects data from every individual in the population.

Sample

A subset of individuals in the population from which we collect data.

Observational study

Observes individuals and measures variables of interest, but does not attempt to influence the responses.

Experiment

Deliberately imposes treatments (conditions) and measures responses.

Convenience sample

Consists of individuals from the population who are easy to reach.

Voluntary response sample

Consists of people who choose to be in the sample by responding to a general invitation.

Bias

Occurs when the design of a statistical study is very likely to underestimate or systematically favor certain outcomes.

Random sample

Consists of individuals from the population who are selected for the sample using a chance process.

Undercoverage

Occurs when some members of the population are less likely to be chosen or cannot be chosen for the sample.

Nonresponse

Occurs when an individual chosen for a sample cannot be contacted or refuses to participate.

Response bias

Occurs when there is a consistent pattern of inaccurate responses to a survey question.

Simple random sample

A sample of size $n$ chosen in such a way that every group of $n$ individuals in a population has an equal chance of being selected as the sample.

Sampling variability

The concept that different random samples of the same size from the same population produce different estimates.

Strata

Groups of individuals in a population that share characteristics thought to be associated with the variables being measured.

Stratified random sampling

Selects a sample by choosing a simple random sample (SRS) from each stratum and combining the SRSs into one overall sample.

Cluster

A group of individuals in the population that are located near each other.

Cluster random sampling

Selects a sample by randomly choosing clusters and including each member of the selected clusters in the sample.

Systematic random sampling

Selects a sample from an ordered arrangement of the population by randomly selecting one of the first $k$ individuals and choosing every $k^{\text{th}}$ individual.

Distribution

Tells us what values a variable takes and how often it takes each value.

Frequency table

Shows the number of individuals having each data value.

Relative frequency table

Shows the proportion or percentage of individuals having each data value.

Bar chart

Displays each category as a bar, where the heights of the bars show the category frequencies or relative frequencies.

Pie chart

Displays each category as a sector of a circle.

Two-way table

A table of frequencies that summarizes the relationship between two categorical variables for some group of individuals.

Side-by-side bar chart

Displays the distribution of a categorical variable for each value of another categorical variable.